- System can handle more load or increase performance by adding more resources.
- Vertical scaling (Scale up)
- Add more resources (CPU, memory, etc.) into a single node.
- Horizontal scaling (Scale out)
- Add more nodes into a system.
- Vertical scaling has a hard limit (It is impossible to add unlimited CPU and memory to a single server).
- Vertical scaling doesn't have failover and redundancy.
- The overall cost of vertical scaling is high.
- Loose coupling
- Decouple different components of the system so they can be scaled independently.
- Horizontal scaling
- Distribute the load across multiple servers or nodes.
- Asynchronous processing
- Offload time-consuming and resource-intensive tasks to background processes or worker queues.
- Caching
- Implement caching strategies to reduce the load on the database or other data sources.
- Database scaling
- Employ database scaling techniques, such as sharding, replication, and partitioning, to distribute data across multiple database servers.
- Use database clustering solutions to manage high availability and failover.
- Auto-scaling
- Set up auto-scaling mechanisms that automatically adjust the number of servers based on metrics like CPU usage, request rate, or other performance indicators.
- Considering scalability from the start
- Design your system with scalability in mind from the beginning.
- Load testing and profiling
- Continuously perform load testing to identify performance bottlenecks and areas that need optimization.
- Use profiling tools to analyze and fine-tune the performance of critical components.